Flax fibre quality and influence on interfacial properties of composites
Bibliographic record
Abstract
Flax fibre holds the potential to serve as an alternative to glass fibre as reinforcement in composite applications. To fully achieve this, the interaction between fibre and matrix must be improved and more consistently controlled. Only then will industry accept natural fibres as a sustainable engineering material choice. Traditionally, interfacial strength improvement has been accomplished through expensive and time consuming chemical surface modification(s). To achieve improved market potential and viability, new methods of developing composite ready flax fibre must be researched and developed through an assessment of the impact of fibre traits for unmodified fibre. Metal, fungal, bacterial, wax and glucose content were examined in this study to determine their correlative effects upon interfacial adhesion, as were fibre characteristics such as colour, density, fineness, fibreshape thickness, conductivity and pH levels. Composite performance was evaluated using fibre pullout and interfacial shear strength tests. These first attempts at correlating as-received flax fibre traits and resulting flax fibre composite properties contain the initial steps towards identifying key flax fibre characteristics that influence composite performance so that proper growth and fibre processing approaches can be developed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".